Turning data into actionable information is a daily challenge for a number of professionals. Numerous entities including military personnel, emergency responders, business analysts and corporate security officers need effective ways to turn data into the information needed to act decisively. Actionable information enables a decision to be made and action is prompted as a result. In contrast, non-actionable information does not result in an immediate response or action.
An example of providing actionable information in a military context is a war-fighter on the ground who communicates with a system to inquire: “I am here, what threats have you seen within the last 10 minutes that can detract me from my objective, where did they come from, and should I engage them or avoid them.”
The increase in the amount of data that can be taken into account to produce actionable information has led to the development of a new generation of information management applications capable of selective information dissemination where, the data is filtered to match client interests with available information.
Such systems can use event-based architectures such as publish-subscribe systems (hereinafter referred as “pub/sub systems”). In pub/sub systems, content producers (systems and end-users) publish messages (events) and content consumers (end-users and software applications) receive them if the message pertains to their interest described by means of a subscription. The system matches incoming messages against the subscriptions and forwards to content consumers just the messages that match the corresponding subscription. Early pub/sub systems were subject-based. In these systems, each message (event) belongs to a certain topic. Thus, subscribers express their interest in a particular subject and they receive all events published within that particular subject. A restriction of these systems can be the limited selectivity of subscriptions. For instance, in Sheth & Perry's 2008 article entitled “Traveling the Semantic Web through Space, Time and Theme,” IEEE Internet Computing, pp. 81-86 in Vol. 12, No. 2, there is described a method for querying spatial and temporal data.
Later pub/sub systems are called content-based systems. In these systems, the subscriptions, constructs that indicate clients' interests, can contain complex queries or event semantics. Ontology is used to represent domain-specific knowledge and allow clients to use the ontology terms to construct subscriptions. Existing content-based and semantic systems have yet to handle rich domain semantics with temporal and geospatial constraints. A trade-off encountered by some systems, for example the one described in the online article by Petrovic, Burcea and Jacobson entitled “S-ToPSS: Semantic Toronto Publish/Subscribe System,” available at http://www.eecg.toronto.edu/˜jacobsen/papers/stopss.pdf, is that by increasing the semantic expressibility of the matching algorithms the system can fail to scale to cope with increasing volume, variety and velocity of incoming data.
Another problem with some systems as demonstrated, for example, in the system described in the article, found online at http://lsdis.cs.uga.edu/lib/download/SAA+2004-PISTA.pdf, by Sheth et. al., 2005, Semantic Association Identification and Knowledge Discovery for National Security Application, is that filtering rules are embedded (hard-coded) in the ontology, making it very difficult to modify them by users as required. Maintaining the rules requires specialized knowledge engineering. This can preclude their effective use in a number of domains. For example, in the military domain rules can be created, updated and tailored by users that cannot deal with the often complex data structures of the ontology.